Schenk Jonas, Marison Ian W, von Stockar Urs
Laboratory of Chemical and Biochemical Engineering, Ecole Polytechnique Fédérale de Lausanne, CH-1015 Lausanne, Switzerland.
Anal Chim Acta. 2007 May 15;591(1):132-40. doi: 10.1016/j.aca.2007.03.056. Epub 2007 Mar 30.
In order to significantly reduce the time involved in mid-infrared spectroscopy calibrations, a novel approach based on a library of pure component spectra was developed and tested with an aerobic Saccharomyces cerevisiae fermentation. Instead of the 30-50 standards that would have been required to build a chemometric model, only five solutions were used to assemble the library, namely one for each compound (glucose, ethanol, glycerol, ammonium and acetate). Concentration profiles of glucose, ethanol and ammonium were monitored with a fair accuracy, leading to standard error of prediction (SEP) values of 0.86, 0.98 and 0.15 g L(-1). Prediction of the two minor metabolites, acetate and glycerol, was less accurate and presented a detection limit of around 0.5 g L(-1). The overall performance of the library-based method proved to be very similar to a 49-standard chemometrics model. The model was shown to be very robust and uncorrelated, since it was able to predict accurately the concentration changes during a spiking experiment. Even though simple, this method allows more advanced calculations, such as determination of the explained variance and detection of unexpected compounds using residuals analysis.
为了显著减少中红外光谱校准所需的时间，开发了一种基于纯组分光谱库的新方法，并在需氧酿酒酵母发酵中进行了测试。构建化学计量学模型通常需要30 - 50个标准品，而该方法仅使用了五种溶液来组建光谱库，即每种化合物（葡萄糖、乙醇、甘油、铵和乙酸盐）各一种。葡萄糖、乙醇和铵的浓度分布监测精度较高，预测标准误差（SEP）值分别为0.86、0.98和0.15 g L⁻¹。对两种微量代谢物乙酸盐和甘油的预测准确性较低，检测限约为0.5 g L⁻¹。基于光谱库的方法的整体性能被证明与49个标准品的化学计量学模型非常相似。该模型显示出很强的稳健性和无相关性，因为它能够在加标实验中准确预测浓度变化。尽管该方法简单，但它允许进行更高级的计算，例如确定解释方差和使用残差分析检测意外化合物。
